Dataset Reuse Indicators Datasets

This dataset contains two files. 1) A python pickle file (github_dataset.zip) that contains Github repositories with datasets. Specifically, using Google’s public dataset copy of Github and the BigQuery service to build a list of repositories that have a CSV or XLSX or XLS file. We then used the GitHub API to collect nformation about each repository in this list. The resulting dataset consists of 87936 repositories that contain at least a CSV, XLSX or XLS file, alongside with information about their features (e.g. number of open and closed issues and license) from GitHub. This corpus had more than two million data files. We then excluded those files withless then ten rows, which was the case for 65537 repositories with a total of 1,467,240 data files. 2) A python pickle file (processed_dataset.zip) containing the feature information necessary to train a machine learning model to predict reuse on these Github datasets Source code can be found at: https://github.com/laurakoesten/Dataset-Reuse-Indicators For a full description of the content see: Koesten, Laura and Vougiouklis, Pavlos and Simperl, Elena and Groth, Paul, Dataset Reuse: Translating Principles to Practice. Available at SSRN: https://ssrn.com/abstract=3589836 or http://dx.doi.org/10.2139/ssrn.3589836本数据集包含两个文件。1) 一个Python pickle格式文件（github_dataset.zip），其中存储了带有数据集的GitHub仓库。具体而言，我们借助谷歌公开的GitHub数据集副本与BigQuery服务，筛选出包含CSV、XLSX或XLS格式文件的仓库列表。随后通过GitHub API收集该列表中每个仓库的相关信息。最终得到的数据集包含87936个至少带有一个CSV、XLSX或XLS文件的仓库，以及这些仓库在GitHub上的相关特征信息（例如未关闭与已关闭议题的数量、许可证类型等）。该语料库包含超过200万个数据文件。随后我们剔除了行数不足10行的文件，此类文件涉及65537个仓库，总计1467240个数据文件。2) 一个Python pickle格式文件（processed_dataset.zip），其中包含用于训练机器学习模型以预测这些GitHub数据集复用情况的必要特征信息。相关源代码可在以下地址获取：https://github.com/laurakoesten/Dataset-Reuse-Indicators。如需了解完整的内容说明，请参阅：Koesten, Laura、Vougiouklis, Pavlos、Simperl, Elena、Groth, Paul所著《Dataset Reuse: Translating Principles to Practice》，可在SSRN平台获取：https://ssrn.com/abstract=3589836 或 http://dx.doi.org/10.2139/ssrn.3589836